---
title: "index"
author: "Daniel Segura"
date: "24/7/2021"
output:
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
---

```{r message=FALSE, warning=FALSE}
library(flexdashboard) 
library(dplyr) 
library(sf) 
library(DT) 
library(plotly) 
library(leaflet) 
library(raster) 
library(ggplot2) 
library(rgdal)
library(tidyverse)
```


 

```{r}
orquideas <- st_read(
  "https://raw.githubusercontent.com/gf0604-procesamientodatosgeograficos/2021i-datos/main/gbif/orchidaceae-cr-registros.csv", 
  options = c(
    "X_POSSIBLE_NAMES=decimalLongitude", 
    "Y_POSSIBLE_NAMES=decimalLatitude"
  ), 
  quiet = TRUE
)

```



```{r}
cantones <-
  st_read(
    "https://raw.githubusercontent.com/gf0604-procesamientodatosgeograficos/2021i-datos/main/ign/delimitacion-territorial-administrativa/cr_cantones_simp_wgs84.geojson",
    quiet = TRUE
  )
```

 

```{r}
provincias <-
  st_read(
    "https://raw.githubusercontent.com/gf0604-procesamientodatosgeograficos/2021i-datos/main/ign/delimitacion-territorial-administrativa/cr_provincias_simp_wgs84.geojson",
    quiet = TRUE
  )
```

```{r}
alt <-
  getData(
    "worldclim",
    var = "alt",
    res = .5,
    lon = -84,
    lat = 10
  )
# Reproyección de la capa de altitud a CRTM05
alt <-
  alt %>%
  projectRaster(crs = 4326)

# Recorte de la capa de altitud con base en la capa vectorial de provincias
altitud <-
  alt %>%
  crop(provincias) %>%
  mask(provincias)
```



```{r}
st_crs(orquideas) <- 4326
```

```{r}
orquideas <- 
  orquideas %>%
  st_join(cantones["canton"])%>%st_join(provincias["provincia"])
```



```{r}
orquideas<- 
  orquideas%>% 
  mutate(coordinateUncertaintyInMeters= as.numeric(coordinateUncertaintyInMeters))%>%
  mutate(eventDate=as.Date(eventDate,"%Y-%m-%d"))

orquideas<- 
  orquideas%>%
  filter(!is.na(coordinateUncertaintyInMeters), coordinateUncertaintyInMeters <= 1000)
```



```{r}
orquideas_species_total <- orquideas %>% group_by(species) %>% count(species)
orquideas_genus_total <- orquideas %>% group_by(genus) %>% count(genus)
orquideas_total <- nrow(orquideas)
```


Registros
=======================================================================

Row
-----------------------------------------------------------------------

### Registros de presencia {.value-box}

```{r cantidad-total-registros-presencia}
valueBox(value=orquideas_total,
         caption= "Cantidad total de registos de presencia",
         icon="fas fa-feather",
         color= "#b1ff8a"
)
```


### Cantidad de géneros {.value-box}

```{r cantidad-total-generos}
valueBox(value=nrow(orquideas_genus_total),
         caption= "Cantidad total de géneros",
         icon="fas fa-spa",
         color= "#d0ea4d"
)
```


### Cantidad de especies {.value-box}

```{r cantidad-total-especies}
valueBox(value=nrow(orquideas_species_total),
         caption= "Cantidad total de especies",
         icon="fas fa-spa",
         color= "#ffc24d"
)
```

Row
----------------------------------------------------------------------
### Registros de presencia

```{r tabla-DT}
orquideas%>%
  st_drop_geometry()%>% 
  dplyr::select(species, eventDate, stateProvince, canton)%>%
  datatable(colnames = c("Especies","Fecha", "Provincia", "Cantón"),
            options = list(
              pageLength=5,
              language= list(url= "//cdn.datatables.net/plug-ins/1.10.11/i18n/Spanish.json")
            )
  )
```

### Grafico pastel

```  {r gráfico-1}
sorted_orq <- 
  orquideas_species_total %>% 
  filter(!is.na(species), species != "") %>% 
  arrange(desc(n))

blank_orq <- orquideas_species_total %>%
  st_drop_geometry() %>% 
  filter(is.na(species)| species == "")
blank_orq$species <- "Otras"
top_10 <- sorted_orq %>% slice(1:10)
others_orq <- sorted_orq %>%
  st_drop_geometry() %>%
  slice(11:n()) %>% merge(blank_orq, all = TRUE) %>% summarize(n = sum(n), species="Otras")

top_orq <- merge(top_10, others_orq, all = TRUE)

Grafi_pie<- data.frame("categorie"= rownames(top_orq), top_orq)
datos<-Grafi_pie[, c("categorie", "species", "n")] 

plot_ly(
  datos,
  labels= ~species,
  values= ~n,
  type = "pie"
)%>%
  layout(
    title="Cantidad de registros por especie y porcentaje de orquideas",
    xaxis= list(
      showgried= FALSE,
      zeroline= FALSE, 
      showticklabels= FALSE
    ),
    yaxis= list(
      showgried= FALSE,
      zeroline=FALSE,
      showticklabels= FALSE)
  )
```


Datos
=======================================================================

Row
----------------------------------------------------------------------


### Mapa Capa leaflet agrupada (clustered) 
  
```{r mapa}
orquideas$species[orquideas$species == ""] <- "Otras"

orquideas_especies <-
  orquideas %>%
  group_by(provincia) %>%
  summarize(especies = n())

# Paleta de colores
colores_registros <-
  colorNumeric(
    palette = "YlGnBu",
    domain = orquideas_especies$especies,
    na.color = "transparent"
  )

# Plantilla de raster
raster_plantilla <-
  altitud %>%
  aggregate(fact = 12)

# Rasterización
orquides_raster_especies <-
  rasterize(orquideas,
            raster_plantilla,
            field = 1,
            fun = "count")

# Paleta de colores para celdas
raster_pal <-
  colorNumeric(
    c("#9ac121", "#d2ff46", "#e7ff2c", "#f5ff62", "#f4ff9f", "#f4ffd1"),
    values(orquides_raster_especies), 
    na.color = "transparent"
)

# Mapa Leaflet
leaflet() %>%
  addTiles(group = "OSM") %>%
  addCircleMarkers(
    data = orquideas,
    stroke = F,
    radius = 4,
    fillColor = "#e66a95",
    fillOpacity = 1,
    popup = paste(
      paste(
        "Provincia:",
        orquideas$provincia
      ),
      paste(
        "Especies:",
        orquideas$species
      ),
      paste(
        "Cantón:",
        orquideas$canton
      ),
      paste(
        "Fecha:",
        orquideas$eventDate
      ),
      sep = '
'
    ),
    clusterOptions = markerClusterOptions(),
    group = "Clustered"
  ) %>%
    addRasterImage(
    orquides_raster_especies,
    colors = raster_pal,
    opacity = 1,
    group = "Celdas"
  ) %>%
  addProviderTiles(providers$OpenStreetMap.Mapnik, group = "OpenStreetMap") %>%
  addProviderTiles(providers$Stamen.TonerLite, group = "Stamen Toner Lite") %>%
  addProviderTiles(providers$Esri.WorldImagery, group = "Imágenes de ESRI") %>%
  addLayersControl(
    baseGroups = c("OpenStreetMap", "Stamen Toner Lite", "Imágenes de ESRI"),
    overlayGroups = c("Clustered", "Celdas")
  ) %>%
  addLegend(
    pal = raster_pal,
    values = values(orquides_raster_especies),
    position = "bottomright",
    title = "Cantidad de 
especies
por celda",
    group = "Registros-Orquideas"
  )
```